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Scientific Literacy for a Knowledge Society

Glen Aikenhead Professor Emeritus

University of Saskatchewan, Saskatoon, Saskatchewan, Canada

Graham Orpwood Professor Emeritus

York University, Toronto, Ontario, Canada

Peter Fensham Emeritus Professor Monash University, Australia, and

Adjunct Professor Queensland University of Technology, Australia

Published as: Aikenhead, G.S., Orpwood, G., & Fensham, P. (2011). Scientific literacy for a knowledge society. In C. Linder, L. Ostman, D.A. Roberts, P-O. Wickman, G. Erickson, & A. MacKinnon (Eds.), Exploring the landscape of scientific literacy (28-44). New York: Routledge, Taylor and Francis Group.


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Glen Aikenhead, Graham Orpwood, and Peter Fensham

The role of science education in preparing students for the world of work was

taken seriously by OECD (1996a,b) when it launched studies on how the world of

work was changing, especially in science-related occupations. At about the same

time, the Royal Society for the Arts, Industry, and Commerce initiated a similar

study in Britain (Bayliss, 1998). Together these studies found that the nature of

work in developed countries has changed in three ways: in kind, in the

requirements for performance, and in the lack of permanence of one’s

engagement. These changes in the world of employment are driven by new forms

of information technology, design requirements, and technology transfer. For

example, oral and written literacies are no longer adequate; digital literacy is a

new essential. The resulting new knowledge enables innovation of processes and

products, locally and globally.

This new knowledge is increasingly becoming a primary source of

economic growth in knowledge-based economies. Taken together, these changes

characterize a Knowledge Society (Gilbert, 2005). A knowledge-based economy

and a Knowledge Society create a need to re-examine SL in developed countries.

The chapter begins with an account of the features of a knowledge-based

economy and a Knowledge Society, as these features affect the interpretation of

SL. A policy position about SL-in-action is developed and analyzed in terms of

considerations that would confront decision makers who determine school science

curriculum policy. Special attention is paid to the choices that exist in types of

school science content, and to the powerful influence of educational assessment

practices.

A Knowledge-Based Economy


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In a knowledge-based economy, knowledge takes three forms: codified, tooled,

and personal (Chartrand, 2007). Codified knowledge is communicated in many

different forms as meaning. Both sender and receiver must know the code if the

message is to convey semiotic or symbolic meaning (Foray & Lundvall, 1996).

Newly codified knowledge is often converted into legal property held by a

company or institution: property that can be bought and sold through copyright.

Tooled knowledge is also communicated in many different ways but

always as function (Chartrand, 2007). It is often protected by patents. Tooled

knowledge takes two forms: hard and soft. Hard tooled knowledge is a physical

implement or process that manipulates or responds to matter-energy. A scientific

instrument is tooled knowledge that can extend human perception into domains

referred to as electrons, quarks, galaxies, and the genomic blueprint of life, for

instance. To accomplish this, scientific tools probe beyond human perception to

produce numbers, which are often converted into graphics. Numbers and graphics

are in turn treated by scientists and technologists as observations. Thus, many

scientific observations today involve a cyborg-like relationship between a human

and an instrument – “instrumental realism” (Ihde, 1991). Soft tooled knowledge,

on the other hand, includes the standards embedded in an instrument (e.g., its

designed voltage – 12, 110, or 220), as well as the instrument’s programming, its

operating instructions, and the techniques required to optimize its performance.

Technology transfer, a key process in economic growth, involves tooled

knowledge (soft and hard) being transferred from one company or institution to

another.

Personal knowledge contrasts with both codified and tooled knowledge

due to the fact that personal knowledge consists of bundles of memory and trained

reflexes of nerve and muscle of a scientist, engineer, or technician (Chartrand,

2007; Foray & Lundvall, 1996). Importantly, some personal knowledge can be


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codified or tooled, but some inevitably remains tacit (Polanyi, 1958). Personal

knowledge is legally protected as know-how.

Ultimately, however, all knowledge in a knowledge-based economy is

personal knowledge because without a human to decode or push the right buttons,

codified and tooled knowledge remain meaningless or functionless (Foray &

Lundvall, 1996). This has implications for science education in a society

propelled by a knowledge-based economy. It means that a country’s knowledge-

based economy relies, in part, on its people and their ability to code and decode

semiotic or symbolic meaning and machine-instrument function. This know-how

is one indicator of competitiveness in the global economy, and thus it is an

important consideration for SL in a knowledge-based economy.

A country’s scientific and technological know-how is characterized by a

blend of knowledge and action. Codified knowledge is about communicating;

tooled knowledge (soft and hard) is about functioning; and personal knowledge is

about participating in some way in the economy. The purpose of ‘knowing’ and

‘having knowledge and know-how’ is thus linked to innovation in science-related

occupations.

In the context of a knowledge-based economy, it is evident that the

disciplines of science and technology are socially interrelated to such an extent

that they form one heterogeneous domain – “technoscience” (Désautels, 2004;

Fleming, 1989). For instance, R&D (research and development) is a conventional

form of technoscience. Désautels, among others, has argued for this broader focus

in school science. In this chapter, we adopt Désautels’s technoscience formulation

and draw on Hurd (1998) in designating technoscience as “science-technology”

(ST).

Any perspective on SL that restricts its meaning to codified scientific

knowledge will be inadequate for students’ future participation in their country’s


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knowledge-based economy. Such a perspective ignores tooled and personal

knowledge, and it ignores technology.

A Knowledge Society

When the engine of a country’s economy is knowledge-based, we have a

Knowledge Society, in which the meaning of wealth creation has changed.

“Where wealth was once related to resources and industrial processes, it is now a

consequence of ever-renewing knowledges necessary to innovate, design,

produce, and market products and service” (Carter, 2008, p. 621).

In an earlier work about the Knowledge Society, Gilbert (2005) explored

the educational implications of these societal changes, based on a comparison to

existing conditions in most educational systems:

1. knowledge is about acting and doing to produce new things, rather than

being only an accumulation of established information; and

2. what one does with knowledge is paramount, not how much knowledge

one possesses.

Consequently in a Knowledge Society, value is associated with:

1. knowing how to learn, knowing how to keep learning, and knowing when

one needs to know more, rather than knowing many bits of content from a

canonical science curriculum;

2. knowing how to learn with others, rather than only accumulating

knowledge as an individual;

3. using knowledge as a resource for resolving problems rather than simply

as a catalogue of ‘right’ answers; and

4. acquiring important competences (skills) in the use of knowledge, rather

than only storing it.

Change is the norm in a Knowledge Society. It follows that learning in such a

society should have a dynamic character that equips students to adapt to change,


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to generate new knowledge, and to continue to improve performance (Bybee &

Fuchs, 2006; Fraser & Greenhalgh, 2001).

Implications for SL

A Knowledge Society relies on expertise in science-technology (ST) employment,

and on the capacity of its citizens to deal with ST-related situations in their

everyday lives. Participation in a Knowledge Society by employers, employees,

and citizens calls for knowledge to be treated in conjunction with acting –

‘knowing-in-action’ – and not as stored facts, abstractions, and algorithms. Both

expert knowledge and citizen knowledge are reconceptualized in this chapter in

terms of ST knowing-in-action.

Some research programs in science education already support a

Knowledge Society. These programs treat knowledge as contextualized social

action – knowing-in-action. For example, Gaskell (2002) maps out partnerships

between science education and industry, in which “knowledge is to be learned in

the context of doing … ‘working knowledge,’ as opposed to abstract propositional

knowledge” (p. 64). Further examples include research programs described by

Roth and Calabrese Barton (2004) and by Roth and Lee (2004), and informed by

activity theory associated especially with Lave and Wenger (1991).

Competence at ST knowing-in-action (i.e., competence at ST-related work

skills or competence in resolving ST-related events and issues) is not simply a

matter of ‘applying’ knowledge mastered in a conventional science classroom. A

curriculum change, and thus a curriculum policy change, is required. Most science

content in the typical curriculum is not directly useable in ST-related occupations

and everyday situations. There are several reasons for this, established by research

on situated cognition: “Thinking … depends on specific, context-bound skills and

units of knowledge that have little application to other domains” (Furnham, 1992,

p. 33).


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The first reason is that a conventional science curriculum’s content must

be deconstructed and then reconstructed and integrated into the idiosyncratic

demands of the specific everyday context (Jenkins, 1992; Layton, 1991; Ryder,

2001). “This reworking of scientific knowledge is demanding, but necessary as

socio-scientific issues are complex. It typically involves science from different

sub-disciplines, knowledge from other social domains, and of course value

judgements and social elements” (Kolstø, 2000, p. 659).

Second, school knowledge tends to be compartmentalized in most

students’ minds, separate from their out-of-school (life-world) knowledge, and the

two sources or knowledge systems simply do not interact (Hennessy, 1993;

Solomon, 1984). The third reason is that science content used in ST-rich

workplaces tends to be procedural scientific knowledge (knowing-in-action),

which is simply different from the propositional knowledge of canonical school

science (Gott, Duggan, & Johnson, 1999; Law, 2002). Because different science

content is applicable in each setting, there is very little transfer of knowledge.

Fourth, the purpose and accountability of the workplace and the science

classroom differ dramatically. Consequently, workplace science is qualitatively

different from school science (Chin et al., 2004).

These established research findings have significant implications for SL as

a curriculum concept. SL in a Knowledge Society is necessarily literacy-in-action

– oral, written, and digital literacy-in-action. Consequently SL as an educational

outcome takes on an active, rather than a passive connotation. SL is not about

‘How much do you know?’ but instead, ‘What can you learn when the need

arises?’ and ‘How effectively can you use your learning to deal with ST-related

events in the work world or the everyday world of citizens?’ The shift in outcome

– from ‘knowing that’ to ‘knowing how to learn and to use this relevant content’ –

would represent a radical shift in school science curriculum policy. At the same

time, it would resonate with the goals for a knowledge-based economy discussed


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by Gilbert (2005), and also by Guo (2007). In short, acquiring knowledge

(‘knowing that’) would be replaced by capacity building (‘knowing how to learn

and knowing-in-action’) as the primary mission for school science. For a

Knowledge Society, the primary meaning for SL becomes SL-in-action.

In terms of Roberts’s Visions I and II of SL (Chapter 1, this volume), our

proposed school science policy position suggests a shift away from Vision I,

given its concentration on theoretical reasoning and its inward-looking focus on

the products and processes of science itself. Instead, ours is an intermediary

position between Visions I and II, but favoring Vision II, given its concentration

on a combination of theoretical, technological, and practical reasoning and its

outward-looking focus on ST-related situations.

SL-in-action requires that students come to understand their ST

knowledge as having a purpose beyond simply ‘knowing that.’ Examples of such

purposes include: getting and keeping ST-related employment, informing daily

activities, analyzing socio-scientific issues, and comprehending global concerns.

As a curriculum concept, SL-in-action is highly promising as a way to increase

the relevance of school science, and to engender habits of life-long learning.

Choosing School Science Content: A Theoretical Framework

Because we treat SL for a Knowledge Society as knowing-in-action associated

with capacity building for life-long learning, we reposition ourselves in this

chapter with respect to what counts as worthwhile knowledge to teach and assess

in science education. To achieve SL-in-action for a Knowledge Society, we

require an innovative way to determine the content, processes, and contexts for

school science. Together this triad will be called “school science content.”

Content without context is ephemeral. Processes without content or context (i.e.,

generic skills) are powerless – a lesson learned from the failure of Science: A

Process Approach, a 1960s elementary science program in the United States, and

its counterpart in the United Kingdom, Science 5-13 (Millar & Driver, 1987).


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We emphasize a distinction between the canonical science content found

in conventional science curricula, on one hand, and on the other hand, relevant

science content – the type of science content actually used by employees in ST-

related occupations and by the public coping with ST-related events and issues. In

short, the distinction is between academic decontextualized knowledge (Roberts’s

Vision I to the extreme) and relevant contextualized knowing-in-action (Vision

II), respectively.

We propose a theoretical framework for school science content based on

two principles: relevance and who decides what is relevant for SL-in-action. The

two principles are depicted in Table 2.1. Who decides what is relevant is

represented in column 1; and column 2 represents, as a consequence, various

types of school science content. Our framework recognizes seven groups of

people who currently decide, or who could reasonably decide, what is to be

included in school science content. The categories, based on the work of Fensham

(2000) and Aikenhead (2006), are not discrete but overlap and interact in various

ways. To work toward achieving SL-in-action for a Knowledge Society,

curriculum developers can draw from several of these categories, and the resulting

curricula will most likely consist of different combinations of categories.

[INSERT TABLE 2.1 HERE]

A conventional school science curriculum emerges from the first category,

“wish-they-knew science” in Table 1. This category embraces the subject matter

of scientific disciplines (the science curriculum). Wish-they-knew science

predominates in Vision I versions of SL.

The other six categories in Table 1 reflect the work world of employers

and employees, as well as the everyday world of citizens, in which ST content

pertains to phenomena and events not normally of interest to most university

science professors (scholarly academics), education officials, and currently many

science teachers. The other six categories represent knowing-in-action, by and


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large, and are therefore supportive of SL-in-action for a Knowledge Society. They

reflect an emphasis on Vision II SL.

Space does not allow us to review the research related to each category in

Table 1 (see Aikenhead, 2006, Ch. 3), but two categories are summarized here,

“functional science” and “have-cause-to-know science.” They clarify suitable

school science content for SL-in-action.

Functional Science

Functional science is the science content that has functional value to ST-

rich employment and to ST-related everyday events. Systematic research has

produced a wealth of general and specific results. For example, industry personnel

placed ‘understanding science ideas’ at the lowest priority for judging a recruit to

their industry. Why? The answer comes from the ethnographic research by

Duggan and Gott (2002) in the United Kingdom, Rodrigues and colleagues (2007)

in Australia, Law (2002) in China, Lottero-Perdue and Brickhouse (2002) in the

United States, and Aikenhead (2005) in Canada. The researchers’ in situ

interviews with people in ST-related occupations indicated that the science

content used by these science graduates in the workplace was so context specific

it had to be learned on the job. High school and university science content was

rarely drawn upon.

Thus, an important quality valued by both employers and employees in

ST-related employment is the capacity to learn ST content on the job. Of course,

school science content for the purpose of preparing students for ST-related

occupations must include science concepts, but the choice of these concepts can

be a functionally relevant choice, not a scholarly academic choice (i.e., opting for

wish-they-knew science). The science content that underpins local contexts of

interest works better for teaching students how to learn and use ST as needed

(Aikenhead, 2006, Ch. 6).


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Have-Cause-to-Know Science

This category represents science content identified by ST experts who

consistently interact with the general public on real-life matters pertaining to ST,

and who know the problems citizens encounter when interacting with these

experts (Fensham, 2002). Out of the diverse research reported in the literature (see

Aikenhead, 2006, Ch. 3), the research program undertaken by Law and her

colleagues (2000) in China clarifies have-cause-to-know science the best. Their

project determined the have-cause-to-know science for two different curricula:

one aimed at citizens’ capabilities at coping with everyday events and issues, and

the other aimed at socio-scientific decision making (Law, 2002; Law et al., 2000).

For the first curriculum, societal experts (e.g., people who work with home and

workplace safety issues; and in medical, health, and hygiene areas) agreed that the

public had cause to know basic scientific knowledge related to an event with

which people were trying to cope, and to know specific applications of that

knowledge (knowing-in-action). Most of all, they should be able to critically

evaluate cultural practices, personal habits, media information, and multiple

sources of conflicting information (Law, 2002). During their interviews, the

experts noted public misconceptions, superstitions, and cultural habits detrimental

to everyday coping.

For Law’s second curriculum (citizens’ participation in socio-scientific

decision making), experts were selected from Hong Kong’s democratic

institutions (the legislature, a government planning department, and a civilian

environmental advocacy group) and were interviewed. The researchers concluded

that the public’s have-cause-to-know science for decision making was very

similar to that required for everyday coping, except socio-scientific decision

making drew upon more complex skills to critically evaluate information and

potential solutions (Law, 2002). The societal experts acknowledged the fact that

socio-scientific decisions often rely more on applying values than on applying


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specific science content, a result duplicated in the United States with academic

scientists at several universities (Bell & Lederman, 2003).

Overall, the Chinese ST experts placed emphasis on a citizen’s capacity to

undertake self-directed learning (life-long learning), but placed low value on a

citizen’s knowing particular content from a typical science curriculum. This result

is similar to the research findings for functional science.

Summary: Pertinent Considerations for Making a Policy Decision

SL that nurtures economic growth requires science education to promote

capacity building in which future workers and savvy citizens learn how to learn

ST as the need arises. Life-long learning for a Knowledge Society ensues. The

school science content essential to achieve this end is not solely “wish-they-knew

science,” but instead any combination of categories of school science content

(Table 2.1) that leads to SL-in-action.

Curriculum policy makers are expected to consider what Deng identifies

as the “institutional” domain of curriculum making (Chapter 3, this volume).

Policy makers can be assisted by considering examples of the implications for the

other two domains Deng identifies: “programmatic” and “classroom.” For

instance, SL-in-action in the programmatic domain is exemplified by:

1. a project that designs context-based school science materials for authentic

ST social practices (Bulte, Chapter xx, this volume), which combined

functional and personal-curiosity science content;

2. a Canadian grade 10 textbook, Logical Reasoning in Science &

Technology (Aikenhead, 1991), which combined functional, have-cause-

to-know, personal-curiosity, and wish-they-knew science content;

3. an AS-level textbook in the United Kingdom, Science for Public

Understanding (Hunt & Millar, 2000), which combined enticed-to-know,

have-cause-to-know, and wish-they-knew science content;


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4. the “public understanding of science” curriculum (Algeme

Natuurwetenshappen) in The Netherlands (De Vos & Reiding, 1999),

which combined have-cause-to-know, need-to-know, and wish-they-knew

science content; and

5. the Science, Technology, Environment in Modern Society project in Israel

(Dori & Tal, 2000), which combined functional, have-cause-to-know, and

wish-they-knew science.

Our SL-in-action policy in the classroom domain is illustrated by, for example:

1. Carlone’s (2003) research program about physics teachers who offered

Active Physics at their school, which combined wish-they-knew,

functional, and personal-curiosity science content; and

2. Kortland’s (2001) research program into students’ learning how to make

decisions in the context of a waste management module, which combined

functional, have-cause-to-know, personal-curiosity, and wish-they-knew

science.

Although concrete examples of program and classroom embodiments are useful to

policy makers, assessment of students’ learning is also a central consideration

.We turn next to an exploration of the role of assessment in science education

reform during the past several decades, and the potential implications for

considering adoption of an SL-in-action policy for school science.

Potential Assessment Issues Surrounding SL-in-Action

Common sense dictates that there should be a strong, clear relationship between

the substance of a curriculum and the assessment of students’ learning based on it.

The relationship can be complex, though, and the complexity becomes more

apparent when the policy represents a considerable change from typical practice,

as indeed SL-in-action would.

Orpwood (2001) recounts two well-known major shifts in science

curriculum policy: the first was a shift to science processes and the structure of


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science in about 1960, and the second was a shift to STS/STSE, beginning early

in the 1980s. In both cases development and acceptance of appropriate assessment

procedures and strategies lagged by about 20 years behind adoption (on paper) of

the new policy. In the former case, Orpwood notes that “The first significant

‘performance assessments’ ... were designed in England in the early 1980s by the

Assessment of Performance Unit (APU, 1983) fully 20 years after the goal of

instilling ‘inquiry skills’ in students had first been introduced into the curriculum”

(p. 143). We also note the 20-year lag regarding the shift to STS/STSE. Only

recently has the Assessment and Qualifications Alliance in England published its

General certificate of education: Science for public understanding 2004 (AQA,

2003). In about the same time frame, OECD’s Programme of International

Student Achievement (PISA) has made available some good examples of how to

assess students on STS/STSE content.

The goal SL-in-action cannot wait 20 years for sufficient assessment

procedures to be developed and implemented, as was the pattern for the previous

two major shifts in science curriculum policy. Events in the world of work could

well marginalize the canonical school science curriculum, making it more

irrelevant than it is currently observed to be, as evidenced in the Statement of

Concern at the beginning of this volume.

In the remainder of this section we offer an analysis of why educational

assessment has such a powerful influence over the selection and implementation

of science curriculum policy. The first part of the analysis examines four

functions of educational assessment and some technical factors (notably validity

and reliability) that are integral to understanding how different kinds of

assessment serve different purposes. The second part is about power distribution

in educational institutions. In the third part we apply these analytical insights to

the case of SL-in-action, with particular reference to potential considerations for

policy makers, educational researchers, and science educators.


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Functions of Educational Assessment

Our first function of educational assessment concerns accountability. The

public, media, and politicians in most Western democracies are increasingly

demanding that education systems and individual schools provide evidence of

their effectiveness, productivity, and ‘value’ for taxpayers’ investment. In some

countries, this has taken the form of ‘league tables’ of schools, based on the

results of examinations designed for other purposes (e.g., GCSE and A levels in

England & Wales). Elsewhere, international assessments such as Trends in

International Mathematics and Science Study (TIMSS) and PISA are used as

proxies for school and system effectiveness. Because of the authority that TIMSS

and PISA command, their reports can have a profound impact on educational

policy despite the very obvious limitations and inadequacies of their paper-and-

pencil character and their objective to transcend local realities (Fensham, 2007).

Finally, in some countries, special tests are designed with this accountability

agenda explicitly in mind. In Canada, for example, the Pan-Canadian Assessment

Program is a case in point.

A key expectation of assessments designed for accountability is the

comparison among schools or school systems. The reliability of the assessment is

therefore very important. For this reason, multiple choice tests are often used

because these can be designed with high reliability for recall of factual

information (i.e., superficial, codified, scientific knowledge, but not tooled

knowledge, nor personal knowledge, nor technological knowledge). Recall is

easier to assess with multiple-choice items than is the more complex knowing

demanded by SL-in-action.

The PISA program was charged with assessing students’ preparedness for

21st century life. Unlike TIMSS, the PISA program is not constrained to be a

narrow test of school curriculum content. In its tests of reading, mathematics, and

science in 2000, 2003, and 2006, PISA has demonstrated that compatibility


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between high reliability and the assessment of more complex knowing-in-action is

possible with the use of a wider variety of item types.

Student certification and selection, a second function of assessment, is

perhaps the most traditional role for assessment. Examinations are used in the

majority of countries throughout the world for the purposes of certifying students’

completion of one stage of education and for selecting them for subsequent

opportunities either in education or employment. This type of assessment can

have the advantage of moving the certification role of education from the school

level to an external (and supposedly impartial) agency level, thus ensuring an

equality of standards countrywide. This advantage, however, becomes a

disadvantage by inhibiting desired changes in curriculum policy and curriculum

implementation when students can only be assessed by these externally designed

assessment instruments, usually the paper-and-pencil type.

When the assessment of more complex goals is included, it has

traditionally been engineered using open-ended or constructed-response items

with the advantages and disadvantages that such items always have. They offer

the student an opportunity to demonstrate their knowledge and skill in more

diverse ways than with multiple-choice items. Thus, open-ended or constructed

response items have greater validity. But reliable (consistent) marking remains a

challenge. Moreover, the assessment is still confined to what can be written

within a fixed (usually short) period of time.

In contrast, our vision of SL-in-action for a Knowledge Society

emphasizes validity as being central to assessment. Students would be given time

to solve a problem and the freedom to draw on a variety of resources, as is the

case in ST-related employment in the everyday world. However, marking these

types of responses requires one-on-one expert observation and evaluation of a

student’s performance. Although this is not impossible – music and dance have


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been evaluated this way for years – it is very rare in a science context, even

though its validity is superior.

School improvement is a third function of educational assessment. Many

people hold a view in which schools whose students achieve well in examinations

are ‘good schools’ and that, correspondingly, schools with lower aggregate results

are poor and are in need of improvement (a view we would argue is misguided).

Assessment is therefore the basis for determining the quality of individual schools

and for measuring whether they are improving.

In the Canadian province of Ontario, for instance, a whole new

government bureaucracy has been developed with a view to improving school

performance to meet government-set targets. On the face of it, this is a good plan.

However, the use of assessment to label schools raises the stakes for schools,

which can, in turn, have an undesirable impact on teaching and learning. In a

recent study, for example, researchers found that some teachers try to avoid

teaching a grade level in which provincial testing takes place; and that, in some

schools, principals discourage teaching subjects that are not tested (Sinclair,

Orpwood, & Byers, 2007).

In any agenda to improve school, assessments that mirror those designed

for accountability can narrow the scope of the curriculum taught, as mentioned

above. School improvement needs to be conceptualized more broadly. While

assessment results can form a component, they should form only part of a broader

description of the character and effectiveness of schools. For example, in the case

of SL-in-action, analyzing the range of activities in which students are engaged

can offer better evidence than statistics based on written tests narrow in scope.

A fourth function of assessment focuses on improving student learning. In

recent years, science educators (e.g., Black & Wiliam, 1998; Bell & Cowie, 2001)

have argued persuasively that the most important purpose for assessment, which

they call ‘assessment for learning’ or ‘formative assessment,’ is also the most


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neglected. Assessment for learning aims squarely at the individual student’s

learning and is designed to have an immediate positive impact on that learning. It

represents the antithesis of the other three approaches to assessment because: it is

individual in its context; it is classroom-based; it is designed and practised

exclusively by teachers; it lacks secrecy – indeed, the sharing of assessment

criteria with students is a key to its success; and its results do not necessarily

require documentation or reporting. It truly implements the view articulated by

Wiggins (1993) that assessment is something we should do with students rather

than to them.

In summary, all four functions of educational assessment are valid in their

own terms. All offer potentially valuable contributions to education and, in an

ideal system, all would have a place. However, political and professional

pressures tend to flavor some over others, and the resulting imbalance can affect

curriculum change. In particular, the choice of assessment function can threaten

the implementation of SL-in-action. Imbalances also create a hierarchy among the

four sets of purposes based in terms of the political and professional power of

those controlling each level of assessment.

Power over Purpose

Senior levels of government typically have the power and resources to

invest more in assessment than lower levels of government, senior bureaucrats

more than junior bureaucrats, and school principals more than classroom teachers.

It follows, therefore, that the needs and interests of the more senior levels will

tend to take precedence over those below them. It is likely that international and

national assessments designed for system accountability or student

certification/selection will have greater power over those designed locally for

promoting student learning. Importantly, the first three functions of educational

assessment have greater power over the fourth function that supports student


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learning. The evidence for the existence of such a hierarchy is the financial

resources devoted to each type of assessment.

For example, in Ontario the results of provincial mathematics and

language assessments are used to make judgments about schools as a whole.

Moreover, the content of these tests have a significant steering effect on the

teaching and assessment carried out by teachers, whether or not this is appropriate

(Sinclair, Orpwood, & Byers, 2007). This hierarchical competition among

functions of assessment also means that reliability-related criteria – critically

important in large-scale and high-stakes assessments – are likely to be of more

significance than validity-related criteria – usually of much greater significance in

the curriculum-related assessments at the school and classroom levels.

The implications for assessment are clear. It is cheaper, simpler, easier,

and more aggrandizing to measure students’ memorization or accumulation of

facts, abstractions, and algorithms than to assess the more complex competencies

that make up a richer vision of SL for a Knowledge Society. Thus, in a

competition for resources, political power wins out over education purpose every

time, and SL-in-action is likely to suffer.

Assessing Knowing-in-Action

If SL-in-action is to become a reality, how should it be assessed when

competence is judged as acting effectively, and assessment is seen as describing

and monitoring that process? For a Knowledge Society, the focus is less on ‘what

you know’ but more on ‘what you can learn and what can you do with it in the

context of the everyday world of work and responsible citizenship.’ Science is

understood in the context of technological and social challenges faced by

individuals and societies.

We propose that assessment move correspondingly away from science

knowledge in a static and de-contextualized sense (traditional assessment), and

even beyond performance assessment with its focus on students’ ability to


20

perform science experiments. Assessment can move toward giving students real-

world tasks where they learn relevant ST content and use this content to achieve a

broader goal.

Real-world tasks can be of two kinds. First, more appropriate for

elementary school, students can be given a simple task that requires the use of

their knowledge, but its use is left to the student to determine. Examples of this

kind of assessment can be found in the Assessment of Science & Technology

Achievement Project (Orpwood & Barnett, 1997). A Grade 1 student who has

been taught about the senses (seeing, hearing, touching, listening, and smelling) is

asked to design a game for students who are blind. A Grade 6 student who has

been taught about methods of heat transmission (conduction, convection, and

radiation) is asked to design a cup that will keep a chocolate drink hot the longest.

Second, more appropriate at a senior level, real-world tasks can be broader

and less concrete. Students can be asked for solutions to societal challenges to

which there may be no right answers (Driver, Leach, Millar, & Scott, 1996). PISA

does include a number of these types of challenges. Functional, have-cause-to-

know, and need-to-know science content can be assessed through students’

analysis of socio-scientific decision scenarios. This is illustrated by the Science

Education for Public Understanding Program (SEPUP, 2003) in the United

States (Thier & Davies, 2001), which explicitly connects its relevant science

content (functional and have-cause-to-know science) to the wish-they-knew

science of the country’s National Science Education Standards (NRC, 1996).

Assessing student decision making on ST-related events and issues has been a

research program in a number of countries (Gaskell, 1994; Kolstø, 2001;

Kortland, 1996; Ratcliffe & Grace, 2003; Sadler, 2009; Zeidler & Sadler, Chapter

yy, this volume). For policy makers, all of these examples are rich sources for

alternative procedures for assessing SL-in-action. These assessment methods go

beyond marking answers as right or wrong, based on their matching a


21

predetermined answer or based on a checklist of predetermined skills. Such

simple methods are contradictory to preparing students for a knowledge-based

economy.

Science students need to be exposed to situations where they can

demonstrate their responses in a scientifically literate manner, and assessment

specialists need to describe and monitor such responses. Because SL-in-action is

‘knowing how to learn and knowing how to use that learning,’ assessment of SL-

in-action must describe and monitor those complex processes.

Conclusion

We succinctly reiterate two crucial concepts – ‘SL-in-action’ and ‘school science

content.’ A Knowledge Society requires employers, employees, and citizens to

develop the capacity to treat knowledge in terms of action – knowing-in-action. In

science education this becomes SL-in-action.

We conceptualize school science content as a triad of scientific content,

processes, and contexts, in which content and processes are invariably context-

bound as they are in the world of employment (i.e., context-bound content and

context-bound processes). This specified meaning for ‘school science content’

harmonizes science education with SL-in-action and ultimately with a Knowledge

Society.

A major implication for policy concerning student assessment logically

follows. Context-bound science instruction and learning are by and large

incompatible with universal assessment ideologies found in many national and

international testing institutions. In the agenda of a Knowledge Society, non-

universal types of assessment for science-technology (ST) learning are given

precedence over issues of accountability, student certification, student selection,

and school improvement.

SL-in-action is about capacity building either for competence in ST-

related occupations, or for resolving ST-related events and issues. If policies,


22

curricula, teacher education programs, teacher professional development, and

student assessment in science education do not support SL-in-action, they hinder a

country’s knowledge-based economy and thereby undermine its Knowledge

Society (Munby, Hutchinson, Chin, Versnel, & Zanibbi, 2003).

We have offered policy makers a theoretical framework for choosing

school science content in line with a Knowledge Society. In addition, we have

clarified an ideology that would guide the development of student assessment

policies that support a Knowledge Society. Current national and international

assessment conventions and practices must give way to new ones so that all

citizens develop a rich range of school science outcomes needed in a Knowledge

Society.

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